CN112299048A - Train loading and distributing system and method based on unmanned grab bucket running mode - Google Patents
Train loading and distributing system and method based on unmanned grab bucket running mode Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G67/00—Loading or unloading vehicles
- B65G67/02—Loading or unloading land vehicles
- B65G67/04—Loading land vehicles
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Abstract
The invention provides a train loading and distributing system and method based on an unmanned grab bucket running mode, wherein a grab bucket running vehicle is enabled to run, a train wagon of a train to be loaded running into a reservoir area is dynamically scanned to obtain laser scanning data, and three-dimensional carriage image data of the train to be loaded are generated according to the laser scanning data; recording the walking position of the grab bucket travelling crane, generating a point-to-point material distribution operation command, executing the material distribution operation command, and recording the weight of each blanking point; acquiring the weight of a grab bucket travelling crane in real time, and recording the blanking amount of the grab bucket in three-dimensional carriage image data each time; and generating a loading model based on the three-dimensional carriage image data, calculating whether the total loading cloth amount of the train to be loaded reaches the rated load or not according to the blanking amount of the grab bucket at each time, if so, ending loading, and if not, continuing loading. The automatic material distribution system realizes unmanned automatic loading and distribution, obviously improves the precision and the flatness of the train loading operation of the travelling train, and improves the production efficiency.
Description
Technical Field
The invention relates to the field of control of logistics transportation processes of bulk cargo yards, in particular to a train loading and distributing system and method based on an unmanned grab bucket traveling mode, which are suitable for full-automatic unmanned train loading operation under the condition of grab bucket traveling for bulk cargo.
Background
At present, grab bucket traveling cranes in the nonferrous metal industry are widely used, the reserve capacity of a bulk cargo field is huge, the grab bucket traveling cranes are mainly used for loading and unloading, dumping and loading, certain operation drivers are required to drive the equipment, and the dust pollution of the bulk cargo field is serious.
In the train loading process, the final loading precision and the flatness depend on the grab bucket material grabbing amount to a great extent, in the unmanned grab bucket control process, the key point of the control on the grab bucket material grabbing amount lies in the opening degree of the grab bucket, in the current project application and test, certain interference exists on the actual grabbing amount due to the stacking height and the drying degree of the bulk materials, if the last bucket in the final loading only needs to load 1 ton, and for the 5 ton grab bucket, 1 ton of bulk materials are accurately grabbed, certain difficulty exists, so that the phenomenon of repeated grabbing occasionally exists, and the precision of the last bucket cannot be achieved in place at one time.
The prior art related to the present application is patent document CN108584467A, an unattended mine area cargo loading and carrying system, a main control system controls a three-dimensional modeling system to scan the appearance of a mineral aggregate accumulation area, store and process point cloud data generated by a laser radar to perform three-dimensional modeling, so as to guide an execution mechanism to grab and send mineral aggregates to a transport carrier of a delivery area, and the three-dimensional modeling system internally comprises a microcomputer which can work independently and is used as a controller, a two-axis cradle head, a GPS and an attitude measurement module; the actuating mechanism comprises an actuating controller, a travelling crane and a grab bucket, the master control system sends grabbing information to the actuating mechanism controller, the actuating mechanism controller controls the travelling crane to move in the two-dimensional horizontal direction to move the grab bucket to the position above a grabbing point, and after the grab bucket finishes grabbing according to the height information of mineral aggregate, the travelling crane moves the grab bucket to a delivery area carrier to load.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a train loading and distributing system and method based on an unmanned grab bucket running mode.
The invention provides a train loading and distributing method based on an unmanned grab bucket running mode, which comprises the following steps:
a compartment identification step: enabling the grab bucket traveling crane to perform walking motion, dynamically scanning a train wagon of a train to be loaded running into a storage area to obtain laser scanning data, and generating three-dimensional carriage image data of the train to be loaded according to the laser scanning data;
a step of distributing the compartment: recording the walking position of the grab bucket travelling crane, generating a point-to-point material distribution operation command, executing the material distribution operation command, and recording the weight of each blanking point;
weighing a grab bucket: acquiring the weight of a grab bucket travelling crane in real time, and recording the blanking amount of the grab bucket in three-dimensional carriage image data each time;
loading and weighing: and generating a loading model based on the three-dimensional carriage image data, calculating whether the total loading cloth amount of the train to be loaded reaches the rated load or not according to the blanking amount of the grab bucket at each time, if so, ending loading, and if not, continuing loading.
Preferably, the car identifying step includes:
dynamic scanning: installing a laser scanning device on a girder of the crane, and dynamically scanning by the laser scanning device when the grab crane moves to obtain laser scanning data;
and a result processing step: preprocessing the laser scanning data to generate regular three-dimensional data, wherein the preprocessing can improve the image resolution of the laser scanning data;
a three-dimensional generation step: and generating complete grid data of all train carriages of the grab car travelling from the regular three-dimensional data, updating the complete grid data in real time, and generating three-dimensional carriage image data in real time.
Preferably, the car warehousing step includes:
vehicle body identification: acquiring the accurate shape-moving position of the traveling crane through a sensor additionally arranged on the traveling crane body;
setting a cloth library: the carriage is enabled to be uniformly provided with a plurality of blanking points in a layered mode, a material taking point is generated for each blanking point, and point-to-point material distribution operation is carried out according to the preset carriage distribution warehouse.
Preferably, the grab bucket weighing step comprises:
controlling the grab bucket: acquiring the weight of the grab bucket in real time, and controlling the opening of the grab bucket according to the weight of the grab bucket so as to control the grabbing amount;
blanking and weighing: and after single material distribution operation, recording the weight of each blanking point, obtaining the net weight of single discharging after removing the tare weight, and recording the net weight of single discharging in the three-dimensional carriage image data.
The invention provides a train loading and distributing system based on an unmanned grab bucket running mode, which comprises the following modules:
a carriage identification module: enabling the grab bucket traveling crane to perform walking motion, dynamically scanning a train wagon of a train to be loaded running into a storage area to obtain laser scanning data, and generating three-dimensional carriage image data of the train to be loaded according to the laser scanning data;
the carriage distribution chamber module: recording the walking position of the grab bucket travelling crane, generating a point-to-point material distribution operation command, executing the material distribution operation command, and recording the weight of each blanking point;
grab bucket weighing module: acquiring the weight of a grab bucket travelling crane in real time, and recording the blanking amount of the grab bucket in three-dimensional carriage image data each time;
loading and weighing module: and generating a loading model based on the three-dimensional carriage image data, calculating whether the total loading cloth amount of the train to be loaded reaches the rated load or not according to the blanking amount of the grab bucket at each time, if so, ending loading, and if not, continuing loading.
Preferably, the car identification module includes:
a dynamic scanning module: installing a laser scanning device on a girder of the crane, and dynamically scanning by the laser scanning device when the grab crane moves to obtain laser scanning data;
a result processing module: preprocessing the laser scanning data to generate regular three-dimensional data, wherein the preprocessing can improve the image resolution of the laser scanning data;
a three-dimensional generation module: and generating complete grid data of all train carriages of the grab car travelling from the regular three-dimensional data, updating the complete grid data in real time, and generating three-dimensional carriage image data in real time.
Preferably, the car garage module includes:
a vehicle body identification module: acquiring the accurate shape-moving position of the traveling crane through a sensor additionally arranged on the traveling crane body;
setting a library module: the carriage is enabled to be uniformly provided with a plurality of blanking points in a layered mode, a material taking point is generated for each blanking point, and point-to-point material distribution operation is carried out according to the preset carriage distribution warehouse.
Preferably, the grapple weighing module comprises:
controlling the grab bucket module: acquiring the weight of the grab bucket in real time, and controlling the opening of the grab bucket according to the weight of the grab bucket so as to control the grabbing amount;
blanking and weighing module: and after single material distribution operation, recording the weight of each blanking point, obtaining the net weight of single discharging after removing the tare weight, and recording the net weight of single discharging in the three-dimensional carriage image data.
Preferably, the point-to-point material distribution operation command is set according to the height of a material discharge position of a train to be loaded in the storage area and the path distance of the grabbing and placing points, and is preferentially set according to the height of the material discharge position.
Preferably, the blanking points are distributed in multiple layers, and when the material distribution of each layer of blanking points is completed, the loading weight is recalculated.
Compared with the prior art, the invention has the following beneficial effects:
the invention realizes unmanned automatic loading and distributing, obviously improves the precision and the flatness of the train loading operation of the travelling train and improves the production efficiency.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
FIG. 1 is a diagram of a train dynamic scanning architecture of the present invention;
FIG. 2 is a schematic representation of a three-dimensional wagon image of the present invention;
FIG. 3 is a schematic view of a cloth point sequence rule of the present invention;
FIG. 4 is a statistical view of the loading model of the present invention;
fig. 5 is a schematic view of the loading process of the present invention.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that it would be obvious to those skilled in the art that various changes and modifications can be made without departing from the spirit of the invention. All falling within the scope of the present invention.
The invention provides a train loading and distributing method based on an unmanned grab bucket running mode, which comprises the following steps:
a compartment identification step: enabling the grab bucket traveling crane to perform walking motion, dynamically scanning a train wagon of a train to be loaded running into a storage area to obtain laser scanning data, and generating three-dimensional carriage image data of the train to be loaded according to the laser scanning data;
a step of distributing the compartment: recording the walking position of the grab bucket travelling crane, generating a point-to-point material distribution operation command, executing the material distribution operation command, and recording the weight of each blanking point;
weighing a grab bucket: acquiring the weight of a grab bucket travelling crane in real time, and recording the blanking amount of the grab bucket in three-dimensional carriage image data each time;
loading and weighing: and generating a loading model based on the three-dimensional carriage image data, calculating whether the total loading cloth amount of the train to be loaded reaches the rated load or not according to the blanking amount of the grab bucket at each time, if so, ending loading, and if not, continuing loading.
Specifically, the car identification step includes:
dynamic scanning: installing a laser scanning device on a girder of the crane, and dynamically scanning by the laser scanning device when the grab crane moves to obtain laser scanning data;
and a result processing step: preprocessing the laser scanning data to generate regular three-dimensional data, wherein the preprocessing can improve the image resolution of the laser scanning data;
a three-dimensional generation step: and generating complete grid data of all train carriages of the grab car travelling from the regular three-dimensional data, updating the complete grid data in real time, and generating three-dimensional carriage image data in real time.
Specifically, the step of arranging the carriages comprises the following steps:
vehicle body identification: acquiring the accurate shape-moving position of the traveling crane through a sensor additionally arranged on the traveling crane body;
setting a cloth library: the carriage is enabled to be uniformly provided with a plurality of blanking points in a layered mode, a material taking point is generated for each blanking point, and point-to-point material distribution operation is carried out according to the preset carriage distribution warehouse.
Specifically, the grab bucket weighing step comprises:
controlling the grab bucket: acquiring the weight of the grab bucket in real time, and controlling the opening of the grab bucket according to the weight of the grab bucket so as to control the grabbing amount;
blanking and weighing: and after single material distribution operation, recording the weight of each blanking point, obtaining the net weight of single discharging after removing the tare weight, and recording the net weight of single discharging in the three-dimensional carriage image data.
The invention provides a train loading and distributing system based on an unmanned grab bucket running mode, which comprises the following modules:
a carriage identification module: enabling the grab bucket traveling crane to perform walking motion, dynamically scanning a train wagon of a train to be loaded running into a storage area to obtain laser scanning data, and generating three-dimensional carriage image data of the train to be loaded according to the laser scanning data;
the carriage distribution chamber module: recording the walking position of the grab bucket travelling crane, generating a point-to-point material distribution operation command, executing the material distribution operation command, and recording the weight of each blanking point;
grab bucket weighing module: acquiring the weight of a grab bucket travelling crane in real time, and recording the blanking amount of the grab bucket in three-dimensional carriage image data each time;
loading and weighing module: and generating a loading model based on the three-dimensional carriage image data, calculating whether the total loading cloth amount of the train to be loaded reaches the rated load or not according to the blanking amount of the grab bucket at each time, if so, ending loading, and if not, continuing loading.
Specifically, the car identification module includes:
a dynamic scanning module: installing a laser scanning device on a girder of the crane, and dynamically scanning by the laser scanning device when the grab crane moves to obtain laser scanning data;
a result processing module: preprocessing the laser scanning data to generate regular three-dimensional data, wherein the preprocessing can improve the image resolution of the laser scanning data;
a three-dimensional generation module: and generating complete grid data of all train carriages of the grab car travelling from the regular three-dimensional data, updating the complete grid data in real time, and generating three-dimensional carriage image data in real time.
Specifically, the carriage library module includes:
a vehicle body identification module: acquiring the accurate shape-moving position of the traveling crane through a sensor additionally arranged on the traveling crane body;
setting a library module: the carriage is enabled to be uniformly provided with a plurality of blanking points in a layered mode, a material taking point is generated for each blanking point, and point-to-point material distribution operation is carried out according to the preset carriage distribution warehouse.
Specifically, the grab bucket weighing module includes:
controlling the grab bucket module: acquiring the weight of the grab bucket in real time, and controlling the opening of the grab bucket according to the weight of the grab bucket so as to control the grabbing amount;
blanking and weighing module: and after single material distribution operation, recording the weight of each blanking point, obtaining the net weight of single discharging after removing the tare weight, and recording the net weight of single discharging in the three-dimensional carriage image data.
Specifically, the point-to-point material distribution operation command is set according to the height of a material discharge position of a train to be loaded in the storage area and the path distance of a grabbing and placing point, and is preferentially set according to the height of the material discharge position.
Specifically, the blanking points are distributed in multiple layers, and after the material distribution of each layer of the blanking points is completed, the loading weight is recalculated.
The hardware system adopted in the image data acquisition of the invention comprises a two-dimensional laser scanner, a driving position positioning coding scale, a network switch, a model operation server and the like. When the travelling crane runs, the travelling crane encoder records the current position data xscan coordinate of the travelling crane in real time, and the two-dimensional laser scanner measures the stock pile polar coordinate information P (rho, theta) in real time. Based on a TCP/IP protocol, the data acquisition module acquires the stockpile distance and the travelling position information in real time at regular sampling time intervals (such as 50ms, which can be set and depends on the lowest frequency of the laser and the travelling code ruler).
In the image data reduction, the scanner coordinate system is reduced to the stock ground coordinate system according to a conversion method of firstly rotating the z axis, then rotating the y axis and finally rotating the x axis. The angles of the above rotations are yaw, pitch, roll, respectively, and the rotation matrix is defined as follows:
the rotation matrix for the transformation between coordinate systems is:
finally, obtaining the three-dimensional coordinate of any point of the stock ground:
wherein: x is the number ofscan、yscan、zscanCoordinates of stock ground data in a scanner coordinate system; x is the number ofadjust、yadjustThe laser is mounted with an offset from the actual coordinate system.
In the splicing and sharing of the image data, the splicing imaging and sharing of the multiple laser scanning imaging data are realized through coordinate reduction and grid-connected processing.
The gridding treatment is to equally divide the XY direction of the whole stock ground into N grids with the same size at the same time, and each grid represents a certain space coordinate range. The smaller the grid, the higher the data accuracy. And restoring the real-time scanning information of each laser scanner into coordinates, and updating the height value of the grids according to the grids to which the coordinates belong, so that the three-dimensional modeling and real-time imaging updating of the whole stock ground data are realized.
And the data denoising is to perform denoising and filtering processing on the grid elevation data, remove and interpolate local abnormity and interference data by considering field interference factors in the data acquisition process.
In order to ensure the accuracy of the three-dimensional grid data, the data is subjected to noise reduction according to the height data range of the stock ground and the actual laser ranging value, the measured data value smaller than the lower limit or larger than the upper limit is eliminated in time, and only the normal data is subjected to grid processing.
Wherein: MaxLength and MaxLength are upper and lower limit values of stock ground height data
The elevation gridding data of the material pile is formed through data noise reduction, coordinate reduction and gridding processing. Therefore, the system updates the data record updating time stamp for each grid, and dynamically monitors the material level updating state of the stock ground reservoir area and the discharging space.
In the material grabbing and taking task recommendation strategy, firstly, a driving material taking task recommendation principle is carried out preferentially according to a high-level area, and a material taking task corresponding to driving is generated dynamically. And (4) carrying out block clustering analysis on the area grids in the high-level area, and carrying out filter block processing on the blocks according to the actual size of the grab bucket. And preferentially acquiring the grid blocks which are close to the current traveling crane to generate a traveling crane material grabbing task point. In order to avoid recommending the material taking task on the inclined plane, after grid blocks are generated according to the level, the method for extracting the characteristic points by the normal vector is utilized to carry out secondary optimization on the material taking task points.
Determining a material taking task point piSet of neighboring points P ═ { P ═ P1,p2,…,pnSolving the gravity center of the block surface
Calculating the normal vector of the least square fitting surface
Computing task point piFluctuation amount of adjacent points
θijIs a point piNormal vector of and its neighboring point pjThe normal vector angle of (a). K is a positive integer, n is a positive integer, and the task points on the inclined plane of the material pile are removed by comparing the positive integer with a set threshold value.
Then, according to a principle that a traveling crane emptying task is recommended preferentially in a low-level region, a corresponding emptying task of a traveling crane is generated to ensure uniform distribution of bulk materials in a reservoir area, the space utilization rate is improved, rope winding of the grab bucket caused by overhigh single pile is avoided, and material loss is reduced.
The high-level and low-level areas are determined according to the height value of the stock dump. For any point data (X)i，j，Yi，j，Zi，j) According to the height threshold value Z, can be obtained
Different height thresholds l correspond to different upper and lower intervals Hmin(l) And Hmax(l) Thereby obtaining different g (l)i，jBecause of g (l)i，jThe value is 0 and 1, namely the three-dimensional space to the two-dimensional plane of the material pile data is realizedAnd (4) dimension reduction treatment.
According to the grabbing area threshold value and the travelling position value of the bulk material grab bucket, comparing the two-dimensional plane area values of the material pile in different intervals and different height ranges, and reasonably recommending corresponding grabbing positions.
As shown in figure 1, the invention combines the train carriage identification and positioning technology, the distribution rule of the carriage bottom layer, the acquisition of the grab bucket grab capacity and the establishment of the loading model. The flatness of the crane loading of the unmanned grab bucket is improved, and the labor intensity of workers is reduced.
In specific implementation, firstly, train carriage recognition is carried out, a laser scanning device arranged on a train girder is driven to dynamically scan train wagons by utilizing the traveling motion of a traveling crane, the obtained laser scanning data is subjected to preprocessing, coordinate conversion, grid normalization processing and interpolation processing to generate regular three-dimensional data, and as shown in fig. 2, complete grid data of the whole train carriage is finally generated, data content in a database is updated in real time, and the generated real-time three-dimensional carriage image data provides data parameter guarantee for the full-automatic train loading process of traveling.
Secondly, implement carriage cloth storehouse, through installing sensor (encoder, coding ruler etc.) on driving a vehicle body additional, obtain the accurate shape position of walking, through the carriage cloth storehouse rule of predetermineeing, as shown in fig. 3, all divide 10 blanking points in the carriage bottom of each section of train, can divide according to different carriage loading weight, guarantee to be far below the loading rated weight). In order to prevent the cloth from being stacked and deflected in the same direction, the following stacking sequence is adopted, 10 points are divided into two layers, the first layer is an odd number point, the second layer is an even number point), point-to-point cloth operation is carried out, each blanking point in the carriage is calculated, the system can automatically generate a material taking point, the coordinate of the material taking point is calculated and generated according to the principle that the high point of the material needing to be loaded in the storage area is prior, and the distance is short and is prior. Wherein the material high point obtains the material level height through installing the laser scanner scanning storehouse district on the driving girder and compares, and the distance is short to grasp according to the same high point and puts a path comparison and obtain. After each blanking, recording the weight of each blanking point, and adopting the principle that the gross weight subtracts the tare weight according to the data of the electronic scale on the car, namely calculating the gross weight once when the grab bucket finishes grabbing, calculating the tare weight once after the grab bucket finishes emptying, and subtracting to obtain the net weight of the emptying.
Then, the grab bucket grabbing amount is obtained, the grab bucket weight is obtained in real time through an on-board electronic scale, if the grab bucket grabbing amount can be controlled by using different grab bucket openness according to needs, if the system automatically judges, when the full-load tonnage of the carriage is very close, loading is completed, and the system automatically issues different grab bucket openness, and small-opening grabbing is achieved through a plurality of gears (controlled through encoders installed on winding drums) of 70%, 50% and the like. When the residual loading weight is less than the rated full bucket weight of the grab bucket, the grab bucket is grabbed by adopting a small opening, for example, a full bucket with 5 tons, when the residual loading weight is less than or equal to 5 tons, the opening of 70 percent is adopted, and when the residual loading weight is less than 3 tons, the opening of 50 percent is adopted. And recording the blanking weight of each hopper in the loading model. The loading model calculates and distributes the next layer of material distribution points and the weight according to the weight, namely, the blanking sequence is selected according to the prior principle that the accumulated weight of the next layer of material distribution points is less according to the weight distribution of the existing loading points.
Finally, as shown in fig. 4, according to the loading model, the weight of each blanking point is recorded, the loading and distributing condition of the train wagon is calculated, that is, according to each blanking weight, the weight distribution condition of the loading blanking points is formed, statistics is performed according to the loading conditions of the previous 10 blanking points, the weights of the two adjacent points are accumulated to be used as a measuring point, the first layer and the second layer are equal 10 blanking points, the third layer is the weight accumulation point of the two adjacent points, the loading model can perform the distributing operation of the previous layer according to the principle that the accumulation amount is least prior, and the unmanned vehicle performs recalculation once when each hopper falls, so that the cycle is performed until the loading weight reaches the rated tonnage.
In the implementation of the invention in a smelting mining area, as shown in fig. 5, when a train needs to be loaded and is driven into a storage area to be in place, the train information is confirmed through a terminal installed on the ground manually, and a command button of 'loading start' is clicked to start to execute the following steps:
and 2, starting to execute the operation instructions of the first layer and the second layer by the unmanned vehicle, and distributing the materials on the train carriages in sequence, wherein 10 points are divided into two layers in the following stacking sequence as shown in fig. 3 so that the materials are not stacked and inclined in the same direction, wherein the first layer is odd points, and the second layer is even points. Simultaneously recording the weight of each blanking point and accumulating the total weight of the loaded truck;
the invention can further carry out unmanned intelligent reconstruction projects, designs the operation flow of grab bucket traveling crane loading, has very high preservation quantity in the metallurgical industry and wide market prospect, and the automatic loading and distributing method can obviously improve the precision and the flatness of the train loading operation of traveling cranes and improve the production efficiency.
Those skilled in the art will appreciate that, in addition to implementing the systems, apparatus, and various modules thereof provided by the present invention in purely computer readable program code, the same procedures can be implemented entirely by logically programming method steps such that the systems, apparatus, and various modules thereof are provided in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Therefore, the system, the device and the modules thereof provided by the present invention can be considered as a hardware component, and the modules included in the system, the device and the modules thereof for implementing various programs can also be considered as structures in the hardware component; modules for performing various functions may also be considered to be both software programs for performing the methods and structures within hardware components.
The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.
Claims (10)
1. A train loading and distributing method based on an unmanned grab bucket running mode is characterized by comprising the following steps:
a compartment identification step: enabling the grab bucket traveling crane to perform walking motion, dynamically scanning a train wagon of a train to be loaded running into a storage area to obtain laser scanning data, and generating three-dimensional carriage image data of the train to be loaded according to the laser scanning data;
a step of distributing the compartment: recording the walking position of the grab bucket travelling crane, generating a point-to-point material distribution operation command, executing the material distribution operation command, and recording the weight of each blanking point;
weighing a grab bucket: acquiring the weight of a grab bucket travelling crane in real time, and recording the blanking amount of the grab bucket in three-dimensional carriage image data each time;
loading and weighing: and generating a loading model based on the three-dimensional carriage image data, calculating whether the total loading cloth amount of the train to be loaded reaches the rated load or not according to the blanking amount of the grab bucket at each time, if so, ending loading, and if not, continuing loading.
2. The train loading and distributing method based on the unmanned grab bucket running mode as claimed in claim 1, wherein the carriage identification step comprises:
dynamic scanning: installing a laser scanning device on a girder of the crane, and dynamically scanning by the laser scanning device when the grab crane moves to obtain laser scanning data;
and a result processing step: preprocessing the laser scanning data to generate regular three-dimensional data, wherein the preprocessing can improve the image resolution of the laser scanning data;
a three-dimensional generation step: and generating complete grid data of all train carriages of the grab car travelling from the regular three-dimensional data, updating the complete grid data in real time, and generating three-dimensional carriage image data in real time.
3. The train loading and distributing method based on the unmanned grab bucket running mode as claimed in claim 1, wherein the carriage distribution step comprises:
vehicle body identification: acquiring the accurate shape-moving position of the traveling crane through a sensor additionally arranged on the traveling crane body;
setting a cloth library: the carriage is enabled to be uniformly provided with a plurality of blanking points in a layered mode, a material taking point is generated for each blanking point, and point-to-point material distribution operation is carried out according to the preset carriage distribution warehouse.
4. The train loading and distributing method based on the unmanned grab bucket running mode as claimed in claim 1, wherein the grab bucket weighing step comprises:
controlling the grab bucket: acquiring the weight of the grab bucket in real time, and controlling the opening of the grab bucket according to the weight of the grab bucket so as to control the grabbing amount;
blanking and weighing: and after single material distribution operation, recording the weight of each blanking point, obtaining the net weight of single discharging after removing the tare weight, and recording the net weight of single discharging in the three-dimensional carriage image data.
5. The utility model provides a train loading cloth system based on under unmanned grab bucket driving mode which characterized in that includes following module:
a carriage identification module: enabling the grab bucket traveling crane to perform walking motion, dynamically scanning a train wagon of a train to be loaded running into a storage area to obtain laser scanning data, and generating three-dimensional carriage image data of the train to be loaded according to the laser scanning data;
the carriage distribution chamber module: recording the walking position of the grab bucket travelling crane, generating a point-to-point material distribution operation command, executing the material distribution operation command, and recording the weight of each blanking point;
grab bucket weighing module: acquiring the weight of a grab bucket travelling crane in real time, and recording the blanking amount of the grab bucket in three-dimensional carriage image data each time;
loading and weighing module: and generating a loading model based on the three-dimensional carriage image data, calculating whether the total loading cloth amount of the train to be loaded reaches the rated load or not according to the blanking amount of the grab bucket at each time, if so, ending loading, and if not, continuing loading.
6. The train loading and distributing system based on the unmanned grab bucket running mode as claimed in claim 5, wherein the car identification module comprises:
a dynamic scanning module: installing a laser scanning device on a girder of the crane, and dynamically scanning by the laser scanning device when the grab crane moves to obtain laser scanning data;
a result processing module: preprocessing the laser scanning data to generate regular three-dimensional data, wherein the preprocessing can improve the image resolution of the laser scanning data;
a three-dimensional generation module: and generating complete grid data of all train carriages of the grab car travelling from the regular three-dimensional data, updating the complete grid data in real time, and generating three-dimensional carriage image data in real time.
7. The train loading and distributing system based on the unmanned grab bucket running mode as claimed in claim 5, wherein the carriage distribution library module comprises:
a vehicle body identification module: acquiring the accurate shape-moving position of the traveling crane through a sensor additionally arranged on the traveling crane body;
setting a library module: the carriage is enabled to be uniformly provided with a plurality of blanking points in a layered mode, a material taking point is generated for each blanking point, and point-to-point material distribution operation is carried out according to the preset carriage distribution warehouse.
8. The train loading and distributing system based on the unmanned grab bucket running mode as claimed in claim 5, wherein the grab bucket weighing module comprises:
controlling the grab bucket module: acquiring the weight of the grab bucket in real time, and controlling the opening of the grab bucket according to the weight of the grab bucket so as to control the grabbing amount;
blanking and weighing module: and after single material distribution operation, recording the weight of each blanking point, obtaining the net weight of single discharging after removing the tare weight, and recording the net weight of single discharging in the three-dimensional carriage image data.
9. The train loading and distributing method based on the unmanned grab bucket running mode according to claim 1 or the train loading and distributing system based on the unmanned grab bucket running mode according to claim 5, wherein the point-to-point distributing operation command is set according to the height of a discharging position of a train to be loaded in a storage area and the path distance of a grabbing and releasing point, and is preferentially set according to the height of the discharging position.
10. The method for distributing the train loaded on the basis of the unmanned grab bucket running mode according to claim 1 or the system for distributing the train loaded on the basis of the unmanned grab bucket running mode according to claim 5, wherein the material dropping points are arranged in a multi-layer mode, and when the material distribution of each layer of the material dropping points is completed, the loading weight is recalculated.
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